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Logic‐gated engineered cells are an emerging therapeutic modality that can take advantage of molecular profiles to focus medical interventions on specific tissues in the body. However, the increased complexity of these engineered systems may pose a challenge for prediction and optimization of their behavior. Here we describe the design and testing of a flow cytometry‐based screening system to rapidly select functional inhibitory receptors from a pooled library of candidate constructs. In proof‐of‐concept experiments, this approach identifies inhibitory receptors that can operate as NOT gates when paired with activating receptors. The method may be used to generate large datasets to train machine learning models to better predict and optimize the function of logic‐gated cell therapeutics. [ABSTRACT FROM AUTHOR]

Background and purpose: Fingolimod is a drug approved for treatment of relapsing‐remitting multiple sclerosis (RRMS) that exerts its effects via sequestering lymphocytes within the lymph nodes. The drug, acting on the sphingosine‐1‐phosphate pathway, is involved in a plethora of processes and, to date, its mechanism of action is not completely understood. Recently, it has been demonstrated that Fingolimod increases the expression of transcription factor NR4A2 in murine brain. NR4A2 belongs to nuclear receptor family 4, group A (NR4A) along with NR4A1 and NR4A3. The role of NR4A2 in the pathogenesis of multiple sclerosis is already known and supported by its down‐regulation observed in blood obtained from patients with RRMS compared with healthy controls (HCs). It is notable that NR4A2 impairment is reversed in patients with RRMS during pregnancy, which represents a transitory state of immune tolerance, associated with reduced disease activity. An inverse correlation between NR4A2 gene expression levels and clinical parameters indicates that more aggressive forms of the disease are characterized by lower levels of NR4A2. Methods: Gene expression levels of NR4A in blood obtained from HCs, treatment‐naive (T0) and Fingolimod‐treated patients with RRMS were evaluated to determine their contribution to drug response. Results: Gene expression levels of NR4A were down‐regulated in T0 patients compared with HCs. Patients treated with Fingolimod for >2 years were characterized by higher levels of NR4A2 compared with the T0 group, approaching those of HCs. NR4A1 and NR4A3 levels were not altered. Conclusions: Involvement of the NR4A family in the pathogenesis of multiple sclerosis and a role of Fingolimod in the recovery from NR4A2 deficit can be hypothesized based on our data. [ABSTRACT FROM AUTHOR]

All cerebellar GABAergic interneurons were derived from a common pool of precursor cells residing in the embryonic ventricular zone (VZ) and migrating in the prospective white matter (PWM) after birth, where both intrinsic and extrinsic factors contribute to regulate their amplification. Among the environmental factors, we focused on Sonic hedgehog (Shh), a morphogen well known to regulate neural progenitor cell proliferation. We asked if and how exogenous Shh treatment affects the lineage of cerebellar GABAergic interneurons. To address these issues, exogenous Shh was administered to embryonic and postnatal organotypic slices. We found that Shh is able to expand the pool of interneuron progenitors residing in the embryonic epithelium and in the postnatal PWM. In particular, Shh signalling pathway was highly mitogenic at early developmental stages of interneuron production, whereas its effect decreased after the first postnatal week. Gene expression analysis of sorted cells and in situ hybridization further showed that immature interneurons express both the Shh receptor patched and the Shh target gene Gli1. Thus, within the interneuron lineage, Shh might exert regulatory functions also in postmitotic cells. On the whole, our data enlighten the role of Shh during cerebellar maturation and further broaden our knowledge on the amplification mechanisms of the interneuron progenitor pool. [ABSTRACT FROM AUTHOR]